LiveKit RAG Assistant

# 💬 LiveKit RAG Assistant v2.0 **Enterprise-grade AI semantic search + real-time web integration for LiveKit documentation** ## 🎯 Features - **Dual Search**: Pinecone docs (3,000+ vectors) + Tavily real-time web - **Standard MCP**: Async LangChain with Model Context Protocol - **Ultra-Fast**: Groq LLM (llama-3.3-70b) sub-5s responses - **Premium UI**: Glassmorphism design with 60+ animations - **Source Attribution**: Full transparency on every answer ## 🚀 Quick Start ```bash # Setup conda create -n langmcp python=3.12 conda activate langmcp pip install -r requirements.txt # Configure .env GROQ_API_KEY=your_key TAVILY_API_KEY=your_key PINECONE_API_KEY=your_key PINECONE_INDEX_NAME=livekit-docs # Terminal 1: Start MCP Server python mcp_server_standard.py # Terminal 2: Start UI streamlit run app.py ``` App opens at `http://localhost:8501` ## 🏗️ Architecture ``` Streamlit (app.py) → MCP Server → Dual Search: ├─ Pinecone: Semantic search on embeddings (384-dim) └─ Tavily: Real-time web results ↓ Groq LLM (2048 tokens, temp 0.3) → Response + Sources ``` ## 🔧 Tech Stack | Layer | Tech | Purpose | |-------|------|---------| | Frontend | Streamlit | Premium glassmorphism UI | | Backend | MCP Standard | Async subprocess | | LLM | Groq API | Ultra-fast inference | | Embeddings | HuggingFace | all-MiniLM-L6-v2 (384-dim) | | Vector DB | Pinecone | Serverless similarity search | | Web Search | Tavily | Real-time internet results | ## 📚 Usage 1. Choose mode: **📚 Docs** or **� Web** 2. Ask naturally: "How do I set up LiveKit?" 3. Get instant answer with 📄 sources 4. Copy messages or re-ask from history ## ⚡ Performance - First query: ~15-20s (model load) - Cached queries: 2-5s - Search latency: <500ms ## 🛠️ Configuration ```env GROQ_API_KEY=gsk_*** TAVILY_API_KEY=tvly_*** PINECONE_API_KEY=*** PINECONE_INDEX_NAME=livekit-docs ``` ## 🔄 Populate Docs ```bash python ingest_docs_quick.py # Creates 3,000+ vector chunks ``` ## 📊 Files - `app.py` - Streamlit UI with premium design - `mcp_server_standard.py` - MCP server with tools - `ingest_docs_quick.py` - Document ingestion - `requirements.txt` - Dependencies - `.env` - API keys ## 🚨 Troubleshooting | Issue | Solution | |-------|----------| | No results | Try web mode or different keywords | | MCP not found | Start mcp_server_standard.py in Terminal 1 | | Slow first response | Normal (15-20s) - model initializes once | | API errors | Verify all keys in .env file | ## � Features ✅ Real-time chat with 60+ animations ✅ Semantic + keyword hybrid search ✅ Copy-to-clipboard for messages ✅ Recent query suggestions ✅ System status dashboard ✅ Chat history persistence ✅ Query validation + error handling --- **Version**: 2.0 | **Status**: ✅ Production Ready | **Created**: November 2025 👨‍💻 **By [@THENABILMAN](https://github.com/THENABILMAN)** | � **Open Source** | ❤️ **For Developers**